User Settings
Open AccessArticle

Computer implemented land use classification with ERTS digital data during three seasons

A. T. Joyce-1974-06-01-NASA STI Repository (National Aeronautics and Space Administration)

TL;DRAbstract

Significant progress has been made in the classification of surface features (land uses) with computer -implemented techniques based on the use of ERTS digital data and pattern recognition software.The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification.After classification, colors are assigned to the various surface features (land uses) classified, and the color-coded classification is film-recorded on either positive or negative 9 1/2" film at the scale desired.Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired.Computer extraction of statistical information is performed to show the extent of each surface condition ( land use) within any given land unit (e.g.training sample, township, county, etc.) that can be identified in the data.Evaluations of the product indicate that classification accuracy is well withi

Chat with Paper

AI Agents for this Paper

Significant progress has been made in the classification of surface features (land uses) with computer -implemented techniques based on the use of ERTS digital data and pattern recognition software.The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification.After classification, colors are assigned to the various surface features (land uses) classified, and the color-coded classification is film-recorded on either positive or negative 9 1/2" film at the scale desired.Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired.Computer extraction of statistical information is performed to show the extent of each surface condition ( land use) within any given land unit (e.g.training sample, township, county, etc.) that can be identified in the data.Evaluations of the product indicate that classification accuracy is well withi

Keywords

Computer scienceEnvironmental scienceRemote sensingLand useGeographyEngineeringCivil engineering

Chat

Click to start Chat